A global shift quantified, not a technological fantasy
The debate on 'the end of work' has long been fueled by futuristic scenarios. Today, the break is less spectacular, but more measurable. On a global scale, employers anticipate a massive reconfiguration of jobs by 2030. The dynamics are not one-dimensional: some roles disappear, others emerge, and increasingly, tasks transition to automated systems. The shock is thus dual: a displacement of roles on one side, transformation of job content on the other.
In this new economy, the unit of account is no longer the 'profession,' but the 'task.' An accountant may not necessarily disappear; some of their tasks will, however. The same goes for a lawyer; yet the drafting, research, and synthesis elements will be reorganized. Fear stems from a simple phenomenon: when 30% or 40% of a role's tasks become automatable, it's not just a gain in productivity; it’s a shift in wage power.
Generative AI does not eliminate jobs everywhere; it primarily undermines specific functions
A common misconception is to think that AI primarily targets blue-collar or unskilled workers. The new wave also impacts graduate segments, especially in roles that are text-intensive, structured, rules-based, and procedural: administrative assistance, customer support, content creation, finance, legal, and compliance. Generative AI excels in areas dominated by language, models, and documents. This is why exposure varies by country: in economies where office work is predominant, exposure is higher; where work is more informal or physical, exposure is lower, but not nonexistent.
This nuance is crucial: exposure does not equal automatic disappearance. A profession can be highly exposed to AI without being 'replaceable' in the short term, due to the inherent responsibility, human interaction, mediation, local context, or simply because the organization has not yet integrated the tool.
Morocco: AI is arriving in an already strained job market
AI does not arrive in a social vacuum. Morocco is already grappling with a structural employment issue, particularly for youth and graduates. This context changes everything: when jobs are tight, automation is not perceived as a technical advancement, but as invisible competition.
Adding to this is a Moroccan paradox: the country aims to accelerate digital skills development and create digital jobs, yet AI simultaneously automates many 'entry-level' tasks that often serve as stepping stones for youth. If businesses harness AI to reduce junior teams, career progression stalls, risking the country producing skills without proportional opportunities.
Competition is not only technological, but also geographical and sectoral
The winners of AI will be those who combine three elements: capital, data, and integration capacity within processes. This is why some countries can convert AI into growth, while others only face social pressure. Between Europe, which has strong regulations, the United States, which industrializes rapidly, and several Asian countries, which balance planning and markets, the battle is as much political as it is economic.
In Morocco, real potential exists in sectors where the country already has roots: exportable services, customer relationship centers, finance, administration, integrated industries, and even niches like the digital creative economy. However, one condition remains: transforming education into concrete employability, and employability into career paths. Without this, AI will only exacerbate an existing divide between insiders and outsiders.
The 'end of work' is a misleading title for a genuine issue: the end of a social model
What is at stake is not the extinction of work, but the erosion of a model: diploma → stable position → progression → retirement. AI accelerates a trend already underway: polarization between highly skilled jobs and low-skilled service roles, with the middle ground contracting. In this economy, the advantage does not only go to those who 'know how to use AI,' but to those who can use it to produce faster, better, and with fewer fixed costs.
The major risk is therefore political: if productivity rises but wages stagnate, if companies profit but individual trajectories are blocked, social tension becomes structural. The question 'who benefits from AI?' becomes as important as 'what can AI do?'
